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REPORTNO CB-R-81-6; ETS-Rg-81-21 DOCUMENT "RESUME ED 209 329 TM 810 871 AUTHOR Breland, HunterM.; Griswold,, Philip A. TITLE Group Comparisons for Basic Skills Measures. INSTITUTION College Entrance Examination Board,.New York,N.Y.;' - t Educational Testing Service, Princeton, N.J. 'a- REPORTNO CB-R-81-6; ETS-Rg-81-21 . PUB RATE' 81 NOTE 35p. : . EDRS PRiCE NW Plus Postage. PC Not Available from EDR§. DESCRIPTORS *Achievement Tests; Asian Americans;'*Basic Skills; Blacks; *Comparative Analysis; Correlation; Higher Education;. Hispanic Americans; Minority Groups; *Predictive Measurement; *Racial Differences; Regression (Statistics); *Sex Differences; Whites IDENTIFIERS English Placement Test; Scholastic Aptitude Test; Test of Standard Written English ,ABSTRACT D Correlation, regression, and score interval analyses . , were conducted for academic tests including theScholastic Aptitude Test (SAT), Test of Standard Written English (TSWE) ,, and foug subtests of the English Placement Test (EPT) for sixdiffetent' groups. The groups were' men, women, Asians,blacks, Hispanics, and ' ,whites. The use of grade point average or individual coursegrades was avoided because these are subjective, often bi&sed, measures.The EPT-Essay score based on a forty-five minutes*ting sample was considered a good standard for comparing other b. sic skills measures available. The measures were evaluated as predic ors ofessay writing and overall performance. The correlational comparisonsshowed few differences across groups, except that correlations tended to be lower for the white sample because of var.ance restrictions. The regression comparisons agreed with previous studies showing blacks and Hispanics,to be generally overpredicted. FalAe negatives,those people who score low on a predictor but who excel on a criterion, occurred least in the,black and Hispanic groups. (Author/DWH) p 1 *********************************************************************** Reproductions supplied by EDRS are the best that can be made *' from the original document. ***!!*********************************************************** ******** 4 US DEPARTMENT OF EDUCATION NATIONAL INSTITUTE OF EDUCATION EDUCATIONAL...RESOURCES INFORMATION College Board CENTER ,ERICI Th.sCO-urne.nt his n rp'o1u en from th pwsr orronlz4, Report On9,nd!rn,4 Morn,' 0,J,yes t11. tA-Po "nip Po nt , 3 -J No. 81-6 05YY ^n'Int f63 y NIE 009' / 7 0 Group CComparisons for Basic Skills Measures Hunter M. Breland Philip A. Griswold PERMISSION TO REPRODUCE THIS MATERIALIN MICROFICHE ONLY HAS BEEN GRANTED BY, , P, K TO TFIE EDUCATIONAL RESOURUES MATION CENTER fEfiqr, tI=.=41- . 4................"....0 , I i Comparisons for Basic Skills Measures Hunter M. Breland. Philip JA. Griswold Educational Testing Service I.. College Board Report No. 81 -6 ETS RR No. 81-21 College Entrance Examination Board, New York, 1981 3 Hunter M. Breland andPhilip A. Griswold are staff members of Educational Testing Service, Princeton, New Jersey. Researchers are encouraged to expfess freely their professional judgment. Therefore, points of view or opinions stated in College Board Reports do not necessarily represent official College Board position or )blicy. The College Board is a nonprofit membership organization that provides tests andother educational services for students, schools, and colleges.The membership is composed oft more than 2,504 colleges, schools, school systems, and educationassociations. Represen- tatives of the members serve on the Board of Trustees and advisory councils and committees that consider the programs of the College Board and participate in the determinationof its policies and activities. Additional copies of this report may be obtained from College Board Publication Orders, Box 2815, Princeton, New Jersey 08541.' The price is $4. Cdf,yright 0 1981 by College Entrance Examination Board. All rights reserved. Pfinted in the United StateL of America. 4 CONTENTS Abstract iv Introduction 1 Instruments 2 Procedures Correlational Analyses Awe 4 Regression Analyses 8 8 . Analyses by Score Levels Summary 17 References 18 Appendixes A. Intercorrelation Matrices B. Regression Analyses: Procedures and Tables 27 1 TABLES 5 1. CorrelatiOns with EPT-Essay Score 5 2. Correlations between the EPT-Reading Score and ATP Scores 6 3. Correlations between the EPT-Sentence Construction Score and ATP Scores 6 4. Correlations between the EPT-Logic and Organization Score and ATP Scores 7 5. Correlations between EPT-Total Score and ATP Scores 6.-Predicting the EPT-Essay. Score and EPT-Total Score from Multiple EPT and ATP Scores 7 7. CoX variance Analyses 10 8. Essay Writing Performance by Group and TSWE Scpre Level 9. Essay Writing Performance by Group and SAT-V Score Level 12 13 10. Esay Writing Performance by Group and EPT-Reading Score 14 11. Essay Writing Performance by Group and EPT-Sentence Construction Score 12. Essay Writing Performance by Group and)OPT-Organization and Logic Score 16 13. EPT-Total Score Performance by Group and TSWE Score Level ii1 5 I ABSTRACT Correlation, regression, end score interval analyses were conducted for six academic measures as predictors, of essay writing and overall performance.,,,( Comparisons for all analyses were made for men, women, Asians, blacks, Hispanics, and whites. Thecor- relatiOnal comparisons showed few differences across giOups, except that correlations tended to be lower for the white sample because of variance restrictions.The re- gression comparisons agreed with previous studies showing blacks and H4panics to bt generally overpredicted. Ori essay-writing. performance, meh were also overpredicted by conventional basic skills measures. In contrast, women tended to write better essays than would have beep predicted by conventional basic skillsmeasures. False negatives, those people who score ,low on a predictor but who excel on a criterion, occurred least in the'black and Hispanic groups. _ A 4 6 iv INTRODUCTION a 11 Because of contemporary concerns about fairness to sex and ethnic groups,it has become customary to conduct analyses of academic tests in use orproposed for use to determine if any unfairness may result from such use. A previous study (Breland, 1977b) reported a number of such analyses for the Test of Standard WrittenEnglish' (TSWE), but this report was limited by the available data. Because of the rela- tively small number of minoiity students in the.sample, it was necessary to combine all minorities into one group for analysis.The present report does not have that limitation. The most common approach to the examination of fairness is to compare correla- tional and regression analyses for,,the various eroups of interest.However, these kinds of analyses do not reveal certain kinds of potential unfairness. For example, they do not examine specific groups of people who may score low on a predictor but who perform satisfactorily if allowed to enter an educational program. Such people have been termed "false negatives." Conversely, there exist groups of students who score high on a predictor but who do not perform satisfactorily later. These have been called "false popitives."When false positives and false negatives are summed, they represent "misses" people for whom an erroneous prediction was made. Cor- ,p relational and regression analyses may not reveal the actual consequences repre- sented in false negyives and false positives. For that reason it is important to examine the bivariate distributions of predictor scores and actual performance measures to.understand better the pytential for unfairness in the use of tests. A second issue in fairness investigations is. whether the outcome being predicted is reliable and unbiased. This concern is commonly referred to as the "criterion problem." The criterion usually used in prediction studies of fairness is the grade point average (GPA). Another useful criterion is performance on some task quite different from the predictor. For example, essays written in English composition courses can be used as a criterion, for comparing performancesfor difrerent groups on multiple- choice tests intended for the prediction ofcollege performance. This kind of criterion has the advantage that it is usually more objective than CPA or specific college course grades especially when essay scores are assigned by readers remote from the instructional setting. Previous studies of some of the same basic skills measures investigated in the present study have been reported by a number' of writers. Breland (1977a) reported an investigation of the Test of Standard WrittenEnglish (TSWE) and, its use in college English placement for four institutions. The institutions provided data on student performance during college, and Educational TestingService matched these data with other data obtained at the time students applied for college. Student performances on essay tests of writing ability were shown to have a strong relation-, ship to student performance on multiple-choice tests of writing ability as repre- sented by the TSWE. Second, the analyses\Andicated that a brief multiple-choice test of writing ability predicted actual ,ifiting performance during thefreshman year of college as well as or better than a brief essay test given atti he beginning of the freshman year. V As noted above, Breland (1977b) compared men, women, minorities, and non- minorities with respect to performance on the TSWE and subsequent performance in English composition courses as well as performance on brief impromptu essays. No important group differences in traditional correlational analyses for
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